Machine Learning Tutorial Python - 13: K Means Clustering Algorithm

K Means clustering algorithm is unsupervised machine learning technique used to cluster data points. In this tutorial we will go over some theory behind how k means works and then solve income group clustering problem using sklearn, kmeans and python. Elbow method is a technique used to determine optimal number of k, we will review that method as well.
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Code: github.com/codebasics/py/blob...
data link: github.com/codebasics/py/tree...
Exercise solution: github.com/codebasics/py/blob...
Topics that are covered in this Video:
0:00 introduction
0:08 Theory - Explanation of Supervised vs Unsupervised learning and how kmeans clustering works. kmeans is unsupervised learning
5:00 Elbow method
7:33 Coding (start) (Cluster people income based on age)
9:38 sklearn.cluster KMeans model creation and training
14:56 Use MinMaxScaler from sklearn
24:07 Exercise (Cluster iris flowers using their petal width and length)
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[@vitaltopics316]

why do we not need to use centroids for the iris dataset?

[@hshrestha2811]

Summarizing the algorithm for K Means clustering based on this video: 1. Start with k centroids by putting them at random points here k =2 2. Compute distance of every point from centroid and cluster them accordingly 3. Adjust centroid so they become center of gravity of given cluster 4. Again recluster every point based on distance with adjusted centroid 5. Reiterate until data points stop changing cluster 6. Again adjust centroids

[@adipurnomo5683]

Noted!

[@akilanebcas2700]

Super

[@mychanneltest8623]

7. done and put the ruler away

[@ganeshn9464]

Please correct me if I am wrong - 2. Compute distance of every point from centroid and cluster them accordingly - This entire process is "built" inside the KMeans.fit_predict(). Correct ?

[@shauryabhatnagar71]

You are probably one of the best teachers I have come across. Thank you so much!

[@arrahman100]

You make Machine Learning so easy to understand. I would say you are a SAVER for the people who are struggling to understand different ML algorithums. Thank you so much. please if possible put some content on NLP.

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All the ML series is so exciting. I'm learning and having fun during the quarantine in Brazil, SP. Thanks, @codebasics

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I have started loving machine learning due to the simplicity of explanations.

[@amilcarc.dasilva5665]

Excellent tutorial. This is highly recommended to watch. Thanks a lot Sir, I find it helpful in my project work....I really appreciate. You have done great work to help others. Keep up doing this great work.

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was trying out tons of videos trying to understand the basics of ML, you made it so simple and quick. Loved it!!

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😊👍

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I looked 5 min at start, and your teaching style for ML is spot on, better than the IIT professors. I am enjoying ML algo now. Thanks.

[@Kingsohio]

This is a great quick refresher for those with the basic knowledge of ML clustering algorithms

[@wyphonema4024]

my grad school professor explains this very badly. You explain things very well with patience, you are the definition of a good teacher

[@codebasics]

glad you liked it :)

[@monfreign]

been researching about these regressions and other methods, have always found myself in your vids, you sir earned my sub :)

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Sir , I found your channel just a week ago and i would just like to thank you so much for such a wonderful content ! Please continue the ML series .. I hope you also make tutorial of Neural Networks and their application!

[@nilupulperera]

What a beautiful explanation. The beauty of Data Science is shown in this video in a remarkable way. The exercise is really beautiful! Thank you very much, Sir.

[@codebasics]

Dear Nilpul, Thanks for the comment. Keep learning. 😂

[@beansgoya]

Fantastic explanation. I like the way you showed us what happens if you don’t scale your features. You also waited for the perfect opportunity to show why we need to use the elbow method.

[@codebasics]

Thanks for your feedback kin. 👍😊 Feedback like this helps me continue do the good things and also any critical feedback is welcome as well as it helps me improve 👍

[@qas4273]

It's a blessing to be able to finally say that I can learn ML, thanks to you :). I have used 'HUE' from seaborn instead of writing plt.scatter for every group of the cluster. sns.scatterplot(df['Age'], df['Income($)'], hue = df['Cluster'])

[@manishsharma2211]

Thanks for this 👍

[@codebasics]

Yes, with seaborn you can do it in one line. Thanks for posting this comment 🙏🏼🙏🏼

[@saratbabum1303]

Nice way of explaining the complicated concept with an example. Great Job !!! Thanks a lot

[@franky0226]

thank you so much ! congrats for 100K !!

[@86Plum]

Amazing video and explanantion! Just started learning about Machine Learning algorithms and this is incredibly helpful. Thank you!

[@praveenjagarlapudi7891]

I have got the real clarity after watching your video, This is a great help. Thank you for all the videos.

[@skyblue021]

This is the best-explained K-means on the internet - period. Thank you!

[@codebasics]

Glad it was helpful!

[@shubhamwaingade4144]

It was good, simple, informative, no errors. I guess these are enough clusters to define the quality of this video.

[@andreabrunelli2030]

Dear CodeBasics, your tutorials are way better than all the classes of the Master in AI I have just completed. Thank you very much!

[@codebasics]

Glad it helped you 😊

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This was awesome! I can't believe I learned how to do K-means clustering in just a few hours. Your explanations are clear and concise. Thank you so much!

[@codebasics]

Glad it was helpful!

[@Ankurkumar14680]

Another excellent video Sir, it is difficult to wait to see your videos on Neural Networks...as you mentioned in the comments below. thanks a ton for your efforts

[@bhaskarg8438]

your explanation is clear and clarity in the content.. and knowledge sharing to needed Data Science community is Nobel... thankyou... 🙏

[@akshrags-mindmaze3407]

7:25 Brilliant Explaination!

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[@amandal8404]

Wow, great intro to cluster analysis in Python. Thank you so much, awesome teaching as always!

[@codebasics]

Glad it was helpful!

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[@maruthiprasad8184]

Optimal value for iris data set got 3. Thank you very much for simple & great explanation.

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The best ML lesson I've ever heard

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The best explanation ever... Thank you so much

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[@codebasics]

Thanks, will do!

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[@codebasics]

Thanks and welcome

[@atifmalayalam4007]

Very clear. Thanks!

[@pnardogan4848]

very well explained. Thank ou for this great tutorial!

[@Milton7141]

As always my friend , excelent video !

[@abhishek4985]

Saw so many videos, but this one video helped the most. Thanks!

[@codebasics]

Glad it helped!

[@sidduhedaginal]

Sir, you made Machine Learners life easy....amazing explanation that ever seen before and by Elbow technique we got K=3 for iris dateset.

[@codebasics]

Thanks for you kind words and I am happy you liked it 😊

[@shubhangiagrawal336]

@@codebasics Sir can you please make one video on knn algorithm? I need it so badly. Thankyou

[@Suigeneris44]

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[@codebasics]

Suigeneris44, I appreciate your comment buddy. I am glad you found this to be useful :)

[@mapa5000]

Outstanding explanation my friend !! Thank you from Houston

[@codebasics]

👍👍😇

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[@sharathkrishnan1558]

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[@spacetimevideostudio109]

Thank you so much Dhaval for this video, with my elbow technique I got k=3. Thanks

[@ramkumars4658]

How will I forget to give a thumbs up?🤣😂.The video was sooo useful and very simple but effective.I understood k-means clustering and Elbow methods.Thank you for posting such a useful video.

[@arulsebastian6338]

Thanks for explaining & exercise. I love this video.

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[@codebasics]

Thanks for your appreciation, sure when I am in India I will plan for a Meetup

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Excellent tutorial sir. Thank you soo much.

[@flyingsalmon]

Fantastic coverage...you covered the basics, then talked about the reasons and potential challenge with real-world data, and showed some amazing methods to visualize differently. Thank you for your continued contribution to learning and sharing with the community. This kind of tutorials is what will make newcomers gravitate toward ML and be glad to learn.

[@codebasics]

Glad you enjoyed it!

[@flyingsalmon]

@@codebasics Absolutely. I do have a follow-up question. I got lost after scaling the values...let me explain. I have a dataset of tips($) and total restaurant bill($) per day per group of customers. I got 3 clusters and they look good after rescaling the bill and tips via MinMax (my x-axis is the bill for food, and y-axis is tips $). But after clustering, I can't tell how to map the x-axis and y-axis rescaled values (which are 0..1 floats) to actual dollar values that are in the dataset. I need to know how the clusters map to real dataset. Is there a way to do that logically? Would really appreciate your input. TY!

[@shara6281]

Thanks a lot, great as all the other videos

[@jakecalhoun1842]

Really clearly explained video thanks!

[@heaven3279]

Excellent quick and short explanation of K-means. Appreciate it

[@codebasics]

Glad it was helpful!

[@vikrampruthvi5]

Thanks a ton... I love your simplicity in explanation and perfection in explaining hurdles that everyone might face. Please keep doing this great work.

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One of the most useful tutorial I have ever seen

[@codebasics]

🤓👍

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You make things quite simple. Please keep posting..

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Thanks a lot for the video. You taught the K-Means Clustering in 10 mins!

[@codebasics]

👍☺️

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Great video. Thank you so much for your help!

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[@codebasics]

Glad you enjoyed it!

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These videos are more helpful than all of the classes I took in my university combined.

[@codebasics]

I am happy this was helpful to you.

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You make every topic so easy to understand. Long time no video, we miss your videos. Please upload video regularly. Once again good to see your videos. Thank u

[@codebasics]

Panda, thanks for your appreciation. I am going through some health issues and that's the reason not able to upload the content on regular basis. I will start uploading once I recover... 🙂

[@pandaparas8500]

@@codebasics oh sorry i m not aware of it.Its ok. Take your time and concentrate on full health recovery . Get well soon sir. Take care. Once again thank u for everything 😊

[@aviralgupta9364]

Fantastic tutorial !!! .Thanks a lot sir ... It gives best explanation

[@ericwr4965]

This was brilliant and I appreciate the explanation of the code. Question, once you get the clusters identified as you took age and income, what would you explain? Would you need the table as well to discuss the pattern as a supplement as otherwise we would just say we have three clusters, but what do they mean?

[@arthuki]

Excellent material!

[@ahmedadnanaziz2005]

what a great explanation , thanks teacher

[@simaykazc1508]

Very clean explanatıons. Thank you. You should be more visible on KZbin!

[@Sheblah1]

this is a perfect introduction to k-means thank you for making this video👌

[@codebasics]

Glad you liked it!

[@alexandermrkich8734]

Excellent, thank you.